Assist Prof Dr. Souvik Das | Artificial intelligence | Excellence in Research
NIT Rourkela, India
Author Profile
Early Academic Pursuits 🎓
Souvik Das’s journey in academia began with a strong foundation in Electrical Engineering, where he pursued his Bachelor of Technology (B.Tech.) at the Regional Computer Centre Institute of Information Technology (RCCIIT) in West Bengal, India, from August 2010 to July 2014. During this period, Souvik demonstrated a keen interest in the technical aspects of electrical systems, which earned him a commendable CGPA of 8.48/10. His academic rigor and curiosity laid the groundwork for his future endeavors in engineering and research.Continuing his academic pursuit, Souvik Das enrolled in the Master of Technology (M. Tech.) program in Industrial Engineering and Management at the prestigious Indian Institute of Technology Kharagpur (IIT KGP) from July 2015 to May 2017. With a CGPA of 8.84/10, he not only excelled academically but also began to refine his research interests, particularly in the areas of human factors, safety engineering, and analytics. This period marked a significant shift in his academic focus, as he started exploring the interdisciplinary nexus of engineering, safety, and human interaction.Souvik’s thirst for knowledge culminated in his doctoral studies, where he pursued a Ph.D. in Safety Engineering and Analytics at IIT Kharagpur from June 2017 to August 2023. His dissertation, titled “Data-Driven Modeling of Cognitive Workload using Eye Tracking Metrics,” underscored his commitment to pioneering research at the intersection of technology and human cognition. Through this work, Souvik contributed valuable insights into understanding how eye-tracking metrics can be leveraged to model cognitive workload, a critical aspect of safety engineering and human factors.
Professional Endeavors 🛠️
Souvik Das’s professional journey is characterized by his roles as a researcher, scholar, and innovator. His career trajectory reflects a consistent dedication to advancing the field of safety engineering and analytics through cutting-edge research and applied projects.From September 2021 to May 2023, Souvik served as the Principal Research Scientist at the Centre of Excellence in Safety Engineering and Analytics (CoE-SEA) at IIT Kharagpur. In this capacity, he played a pivotal role in conceptualizing, planning, and executing innovative projects focused on occupational safety and ergonomics. His work during this period was instrumental in publishing three high-impact journal articles that have contributed to the body of knowledge in safety engineering. Souvik’s ability to collaborate with cross-functional teams and translate research findings into actionable insights also had a significant influence on the development of Industry 4.0 solutions, particularly in enhancing situational awareness in the workplace.In June 2023, Souvik took on the role of Visiting Scholar at the School of Engineering Technology (SOET) at Purdue University, USA. Here, he has been involved in pioneering projects that utilize natural language processing and large language models to analyze vast volumes of accident and incident narratives. This role not only highlights his adaptability to new research environments but also his commitment to applying advanced technologies to solve real-world safety challenges.Additionally, Souvik’s contributions extend to the academic publishing domain, where he has been serving as an Associate Editor for the Journal of Emerging Investigators, Inc., since November 2023. In this role, he is responsible for managing the peer review process, ensuring timely and thorough reviews, and guiding young scientists in transforming their research into formal publications.
Contributions and Research Focus 🔍
Souvik Das’s research interests are diverse and interdisciplinary, encompassing Human Factors and Ergonomics, Safety Engineering and Analytics, Risk Assessment, Virtual and Augmented Reality, Eye Movements Analysis, Artificial Intelligence, and Machine Learning. His work in these areas is underpinned by a strong foundation in both theoretical and applied research methodologies.One of Souvik’s notable contributions is his work on data-driven modeling of cognitive workload using eye-tracking metrics. This research provides critical insights into how cognitive load can be quantified and monitored in real-time, offering significant implications for enhancing safety in various industrial and occupational settings. His work in this area not only contributes to the academic discourse but also has practical applications in improving workplace safety and efficiency.Souvik’s expertise in coding (R, Python, HTML, C++) and his proficiency with a wide range of software tools, including MATLAB, Delmia, LINGO, MINITAB, and SPSS, among others, have enabled him to approach his research with a robust analytical framework. His ability to integrate these tools into his research allows him to tackle complex problems with precision and innovation.
Accolades and Recognition 🏅
Throughout his academic and professional career, Souvik Das has received recognition for his contributions to the field of safety engineering and analytics. His published works in high-impact journals are a testament to the quality and relevance of his research. Additionally, his role as an Associate Editor of a scientific journal further underscores his standing in the academic community, where he is trusted to mentor and guide emerging researchers.
Impact and Influence 🌟
Souvik’s work has had a profound impact on both academic and industrial sectors. His research has influenced the development of safer and more efficient industrial processes, particularly through his contributions to Industry 4.0 solutions. By integrating human factors into safety engineering, Souvik’s work has helped bridge the gap between technology and human interaction, leading to more effective safety protocols and practices.
His influence extends beyond his immediate research environment, as he continues to mentor young scientists and contribute to the academic community through his editorial work and collaborative research efforts.
Legacy and Future Contributions 🧭
As Souvik Das continues his journey as a Visiting Scholar at Purdue University, his future contributions are poised to further advance the fields of safety engineering and human factors. His ongoing projects involving natural language processing and large language models signal a forward-thinking approach to research, where technology is harnessed to address complex safety challenges.Souvik’s legacy will likely be defined by his interdisciplinary approach, his commitment to bridging the gap between research and practice, and his ability to mentor the next generation of researchers. As he continues to explore new frontiers in safety engineering and analytics, his work will undoubtedly leave a lasting impact on both academia and industry.
Citations
A total of 192 citations for his publications, demonstrating the impact and recognition of his research within the academic community.
- Citations 192
- h-index 21
- i10-index 8
Notable Publications
- Title: Assessment of Cognitive Workload Based on Information Theory Enabled Eye Metrics
Authors: Das, S., Maiti, J.
Journal: Safety Science
Year: 2024 - Title: A Semi-Automated Coding Scheme for Occupational Injury Data: An Approach Using Bayesian Decision Support System
Authors: Das, S., Khanwelkar, D.R., Maiti, J.
Journal: Expert Systems with Applications
Year: 2024 - Title: A Novel Classification Approach Based on Context Connotative Network (CCNet): A Case of Construction Site Accidents
Authors: Gupta, A.K., Sai Pardheev, C.G.V., Choudhuri, S., Garg, A., Maiti, J.
Journal: Expert Systems with Applications
Year: 2022 - Title: Eye-Tracking Data as a Way to Detect Sleep Deprivation in an Individual, Based on Attention, Mental Agility, and Problem-Solving
Authors: Das, S., Pratyush, P., Das, D., Maiti, J., Krishna, O.B.
Book: Machine Learning Algorithms for Engineering Applications: Future Trends and Research Directions
Year: 2022 - Title: Reconstruction of 3D Point Cloud Based on the Sequence of Images
Authors: Das, S., Girdharwal, A., Maiti, J., Krishna, O.B.
Book: Machine Learning Algorithms for Engineering Applications: Future Trends and Research Directions
Year: 2022.